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mcp-server-builder

Design and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and TypeScript support, schema validation, safe evolution. Use when exposing an existing API as an MCP server, building tool integrations for Claude or Codex or Cursor, or scaffolding an MCP project from scratch.

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name mcp-server-builder description Design and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and TypeScript support, schema validation, safe evolution. Use when exposing an existing API as an MCP server, building tool integrations for Claude or Codex or Cursor, or scaffolding an MCP project from scratch. MCP Server Builder Tier: POWERFUL · Category: Engineering · Domain: AI / API Integration Overview Use this skill to design and ship production-ready MCP servers from API contracts instead of hand-written one-off tool wrappers. It focuses on fast scaffolding, schema quality, validation, and safe evolution. The workflow supports both Python and TypeScript MCP implementations and treats OpenAPI as the source of truth. Core Capabilities Convert OpenAPI paths/operations into MCP tool definitions Generate starter server scaffolds (Python or TypeScript) Enforce naming, descriptions, and schema consistency Validate MCP tool manifests for common production failures Apply versioning and backward-compatibility checks Separate transport/runtime decisions from tool contract design When to Use You need to expose an internal/external REST API to an LLM agent You are replacing brittle browser automation with typed tools You want one MCP server shared across teams and assistants You need repeatable quality checks before publishing MCP tools You want to bootstrap an MCP server from existing OpenAPI specs Key Workflows 1. OpenAPI to MCP Scaffold Start from a valid OpenAPI spec. Generate tool manifest + starter server code. Review naming and auth strategy. Add endpoint-specific runtime logic. python3 scripts/openapi_to_mcp.py \ --input openapi.json \ --server-name billing-mcp \ --language python \ --output-dir ./out \ --format text Supports stdin as well: cat openapi.json | python3 scripts/openapi_to_mcp.py --server-name billing-mcp --language typescript 2. Validate MCP Tool Definitions Run validator before integration tests: python3 scripts/mcp_validator.py --input out/tool_manifest.json --strict --format text Checks include duplicate names, invalid schema shape, missing descriptions, empty required fields, and naming hygiene. 3. Runtime Selection Choose Python for fast iteration and data-heavy backends. Choose TypeScript for unified JS stacks and tighter frontend/backend contract reuse. Keep tool contracts stable even if transport/runtime changes. 4. Harden for Production Key items before publishing: Keep secrets in env vars, not tool schemas Prefer outbound host allowlists over open proxies Use additive-only changes; never rename tool names in-place Full hardening guidance: references/production-hardening-guide.md . Script Interfaces python3 scripts/openapi_to_mcp.py --help Reads OpenAPI from stdin or --input Produces manifest + server scaffold Emits JSON summary or text report python3 scripts/mcp_validator.py --help Validates manifests and optional runtime config Returns non-zero exit in strict mode when errors exist Reference Material references/production-hardening-guide.md — auth & safety design, versioning strategy, common pitfalls, best practices, architecture decisions, contract quality gates, testing strategy, deployment practices, security controls references/openapi-extraction-guide.md references/python-server-template.md references/typescript-server-template.md references/validation-checklist.md README.md
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The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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